Multiple Input Multiple Output (MIMO) communication is becoming an integral part of current and future wireless communication standards. Using multiple transmit and receive antennas, MIMO communications enable multiple data streams to be conveyed simultaneously and independently between the transmitter and the receiver without consuming additional bandwidth or other radio resources. To that end, the transmitter and/or receiver comprise an antenna array having multiple antennas, each associated with a variable antenna weight, where the antenna weights at the transmitter are generally referred to as pre-coders. Through the use of the weighted transmitter and/or receiver antennas, different patterns may be formed for different data streams. If the wireless radio channel exhibits rich scattering, e.g., low correlation or a small singular value spread, then multiple possible propagation paths exist between the transmitter and receiver, allowing different data streams to be transmitted by orthogonal mapping over the different paths.
The receiver must process the received composite signal to separate and decode each of the transmitted data streams. To that end, conventional systems use linear receivers, e.g., minimum mean square error (MMSE) receivers, or non-linear receivers, e.g., maximum likelihood (ML) receivers. The ability of either type of receiver to separate the transmitted data streams present in a received composite signal depends on the orthogonality between the channels of the individual data streams. In general, the separation will not be perfect, leading to inter-stream interference, which limits the achievable signal-to-noise ratio (SNR) or signal-to-interference plus noise ratio (SINR) for each signal stream. The more the data stream channels resemble each other, the more difficult it will be for the receiver to separate the data streams. Channel similarity may be expressed based on the cross-correlation of the channels, through an alternative measure known as the singular value spread (which is derived based on the channel). A large singular value spread indicates highly similar channels, and thus, a difficult receiver problem. Therefore, the best conditions for MIMO communications occur when the SNR or SINR is high and the wireless channel experiences rich scattering, as indicated by low correlation or a small singular value spread.
Unfortunately, to some extent the beneficial channel conditions for MIMO are mutually exclusive, meaning the highest SNR or SINR conditions often occur at the same time as the lowest experienced channel richness, and vice versa. This problem may be exacerbated when one or more dominant data streams overpower weaker multi-path data streams. As used herein, a dominant data stream or a dominant signal path is defined as the data stream or path associated with a dominant mode, a dominant eigenmode, and/or a line-of-sight (LOS) path. For example, a large singular value spread or a large amplitude difference between the data streams in the received composite signal (e.g., due to a dominant LOS data stream) may cause some of the weaker data streams to end up with low SNRs. In response, the receiver may try to optimize the throughput by requesting a lower rank transmission (i.e., to reduce the number of data streams) to avoid wasting power on data streams where little to no throughput is expected, and by requesting a power increase for the data streams where the SNR gain will translate into improved throughput.
Requesting a power increase, however, can exacerbate noise conditions proportional to or dependent on the signal strength, i.e., multiplicative noise, particularly when such noise conditions limit the throughput conditions. Further, the use of fewer data streams leads to lower peak data rates over the wireless connection, which is expected to become even more problematic as standards and technology trend towards transmitters and receivers capable of handling larger numbers of signal streams. For example, both LTE release 10 and IEEE 802.11 ac have recently standardized up to 8×8 MIMO transmissions. Thus, there remains a need for improving MIMO throughput conditions limited by multiplicative noise.